CodeForces-208C Police Station

本文针对一个涉及图论的问题,提出了一种高效的算法解决方案。该问题要求计算从城市1到城市n的所有最短路径中,通过设立警察局使路径变为安全路径的平均数量。文章详细解释了如何使用SPFA算法来找出所有最短路径,并通过动态规划记录路径数量。

题目:

            https://cn.vjudge.net/problem/CodeForces-208C


大意:

           有n个城市,编号为1-n,有m条双向路,现要在一个点设立警察局,通过这个点的路就是安全路,求1到n的每条最短路上平均的安全路的条数,即安全路总可能条数/总最短路条数。


思路:

     题目比较难理解,吃了英语的亏,首先是安全路总可能条数,在点2-n-1中某个点x建警察局,则在每条最短路中会产生2条安全路,在x点建立警察局所产生的总条数就是1到x的路径*x到n的路径;总最短路条数便是1到n的所有最短路条数,于是可以用spfa计算最短路,dp记录条数。另外要注意最短路和条数要使用long long,否则会载在Test 22,因为假设六个一组形成16个4叉路,剩下四个再形成三叉路,则总最短路条数为2^32*3,大于int范围。(思路比较难理解,建议边看代码边理解)。


代码:

#include<iostream>
#include<algorithm>
#include<cstring>
#include<cmath>
#include<cstdio>
#include<map>
#include<queue>
#include<vector>
#include<set>;
using namespace std;

typedef __int64 ll;
const int inf = 0x3f3f3f;
vector<int> m[105];
ll dis[105], dp[105];
int n, num;

void spfa(int st) {
    for(int i = 1; i <= n; i++) {
        dp[i] = 0;
        dis[i] = inf;
    }
    dis[st] = 0;
    dp[st] = 1;
    queue<int> q;
    q.push(st);
    while(!q.empty()) {
        int now = q.front();
        q.pop();
        for(int i = 0; i < m[now].size(); i++) {
            int to = m[now][i];
            if(dis[to] > dis[now]+1) {
                dis[to] = dis[now] + 1;
                dp[to] = dp[now];
                q.push(to);
            }
            else if(dis[to] == dis[now] + 1) dp[to] += dp[now];
        }
    }
}

int main() {
    //freopen("in.txt","r",stdin);
    int a, b;
    scanf("%d%d",&n,&num);
    for(int i = 0; i < num; i++) {
        cin >> a >> b;
        m[a].push_back(b);
        m[b].push_back(a);
    }
    spfa(1);
    ll len = dis[n], sum = dp[n];
    double ans = 1.0;
    for(int i = 2; i < n; i++) {
        spfa(i);
        if(dis[1]+dis[n] == len) ans = max(ans,2.0*dp[1]*dp[n]/(double)sum);
    }
    printf("%.12lf",ans);
    return 0;
}



基于可靠性评估序贯蒙特卡洛模拟法的配电网可靠性评估研究(Matlab代码实现)内容概要:本文围绕“基于可靠性评估序贯蒙特卡洛模拟法的配电网可靠性评估研究”,介绍了利用Matlab代码实现配电网可靠性的仿真分析方法。重点采用序贯蒙特卡洛模拟法对配电网进行长时间段的状态抽样与统计,通过模拟系统元件的故障与修复过程,评估配电网的关键可靠性指标,如系统停电频率、停电持续时间、负荷点可靠性等。该方法能够有效处理复杂网络结构与设备时序特性,提升评估精度,适用于含分布式电源、电动汽车等新型负荷接入的现代配电网。文中提供了完整的Matlab实现代码与案例分析,便于复现和扩展应用。; 适合人群:具备电力系统基础知识和Matlab编程能力的高校研究生、科研人员及电力行业技术人员,尤其适合从事配电网规划、运行与可靠性分析相关工作的人员; 使用场景及目标:①掌握序贯蒙特卡洛模拟法在电力系统可靠性评估中的基本原理与实现流程;②学习如何通过Matlab构建配电网仿真模型并进行状态转移模拟;③应用于含新能源接入的复杂配电网可靠性定量评估与优化设计; 阅读建议:建议结合文中提供的Matlab代码逐段调试运行,理解状态抽样、故障判断、修复逻辑及指标统计的具体实现方式,同时可扩展至不同网络结构或加入更多不确定性因素进行深化研究。
### Codeforces Problem 976C Solution in Python For solving problem 976C on Codeforces using Python, efficiency becomes a critical factor due to strict time limits aimed at distinguishing between efficient and less efficient solutions[^1]. Given these constraints, it is advisable to focus on optimizing algorithms and choosing appropriate data structures. The provided code snippet offers insight into handling string manipulation problems efficiently by customizing comparison logic for sorting elements based on specific criteria[^2]. However, for addressing problem 976C specifically, which involves determining the winner ('A' or 'B') based on frequency counts within given inputs, one can adapt similar principles of optimization but tailored towards counting occurrences directly as shown below: ```python from collections import Counter def determine_winner(): for _ in range(int(input())): count_map = Counter(input().strip()) result = "A" if count_map['A'] > count_map['B'] else "B" print(result) determine_winner() ``` This approach leverages `Counter` from Python’s built-in `collections` module to quickly tally up instances of 'A' versus 'B'. By iterating over multiple test cases through a loop defined by user input, this method ensures that comparisons are made accurately while maintaining performance standards required under tight computational resources[^3]. To further enhance execution speed when working with Python, consider submitting codes via platforms like PyPy instead of traditional interpreters whenever possible since they offer better runtime efficiencies especially important during competitive programming contests where milliseconds matter significantly.
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